Question 1

How do I install Neanderthal with GPU support?

Accepted Answer

You need to install CUDA or OpenCL drivers and configure Neanderthal to use the GPU backend. Refer to the external documentation for platform-specific steps, as setup can be complex and vary by system.

Question 2

Is Neanderthal better than using Java libraries like EJML for Clojure?

Accepted Answer

Neanderthal often outperforms pure-Java libraries due to native optimizations, but if you want to avoid native dependencies, EJML might be simpler for JVM-only environments with less setup hassle.

Question 3

Can I use Neanderthal for deep learning projects?

Accepted Answer

While it provides fast linear algebra primitives, Neanderthal doesn't include neural network layers or training algorithms out of the box. You'll need to implement those yourself, unlike all-in-one frameworks like TensorFlow.

Question 4

How to perform matrix multiplication in Neanderthal?

Accepted Answer

Use the 'mmul' function from the API. First, create matrices with constructors like 'dge', then call 'mmul' with them as arguments. Check the documentation for code examples and best practices.

Question 5

Does Neanderthal work on Windows?

Accepted Answer

Yes, but it requires installing BLAS/LAPACK libraries like OpenBLAS or Intel MKL on Windows, which can be more challenging than on Linux. The documentation provides guidance, but expect some configuration effort.

Question 6

What are the alternatives to Neanderthal in Clojure?

Accepted Answer

Alternatives include core.matrix for a pure-Clojure approach or Java interop with libraries like ND4J. Neanderthal is best for maximum performance with native acceleration, while others trade speed for simplicity.

Neanderthal

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